Presentation on intelligent traffic prediction system
- 1. Presentation on Road Traffic Information using Cellular Networks Presented By Engr. Md. Tanzir Ahsan Id-012152019
- 2. Road Traffic Information INTRODUCTION VIDEO SURVEILLANCE SYSTEMS TRAFFIC MONITORING ISSUES ROAD MAP & TRAFFIC DETECTION CONVENTIONAL & NEW TRAFFIC DATA SOURCES NEW DATA PROVIDERS VEHICLE TRACKING STRATEGIES A REAL TIME SYSTEM EXPLANATION DRAWBACKS
- 3. INTRODUCTION • ROAD TRAFFIC CAN BE MONITORED BY MEANS OF STATIC SENSORS AND DERIVED FROM FLOATING CAR DATA. • THE TRAFFIC INFORMATION OF ROAD CAN BE COLLECTED IN A VARIOUS WAYS, SUCH AS USING ROAD SIDE DETECTORS PUBLIC CALLERS FLOATING CAR DATA LICENSE PLATE MATCHING
- 4. Video surveillance Present Implementations Human detection systems. vehicle monitoring systems. Advantages of video surveillance Keep track of information video data for future use. Helpful in identifying people in the crime scenes etc.. Disadvantages of the present system It’s difficult to maintain heavy amount of raw video data Human interaction. Require higher bandwidth for transmitting the visual data.
- 5. Need for Traffic Monitoring To reduce the traffic congestion on highways Reduce the road accidents Identifying suspicious vehicles. Etc..
- 6. Traffic Monitoring Traffic scene analysis in 3 categories. A strait forward vehicle detection and counting system . Congestion monitoring and traffic scene analysis. Vehicle classification & tracking systems which involve much more detailed scene traffic analysis.
- 7. Road Map and Traffic Detection Uses existing Detection Systems Traffic: qCar, qHGV, vCar, vHGV (per time for every lane) Road Map: Distance between adjacent cross sections (= section), location of ascents, descents, entrances, exits 100100 Central Traffic ComputerLocal ComputerTraffic Detection Traffic Sign Gantry Environmental Detection
- 8. Substitute Values Substitute missing Data by Time-Distance Traffic Forecast use previous cross section to forecast traffic on main and exit lanes use following cross section to forecast traffic on entrance lanes use historical data when neighbor cross section not available 8 0 ! 8 0 q qCar Hgv v vCar Hgv 100100 1 2 3 Time Distance Forecast Detect ariving vehicles at cross section, Trace vehicles during the sector by using detected vehicle speed, calculate number of cars, that arrive at subsequent cross section for observed time interval.
- 9. CONVENTIONAL DATA SOURCES ROAD TRAFFIC SENSORS • INDUCTIVE LOOPS • PNEUMATIC TUBES • PIEZO-ELECTRIC SENSORS • VEHICLE CLASSIFIERS HOUSEHOLD TRAVEL SURVEY TRAFFIC CAMERAS FLOATING CAR SURVEYS
- 10. NEW TRAFFIC DATA SOURCES ROAD-SIDE TRAFFIC SENSORS • ACOUSTIC SENSORS • MICROWAVE RADAR • LIDAR AND ACTIVE INFRARED (SIDE-FIRE) SENSORS • VIDEO IMAGE DETECTION • RADIO FREQUENCY IDENTIFICATION (RFID) TAGS GPS-BASED HOUSEHOLD TRAVEL SURVEYS MOBILE PROBE-TYPE DATA SOURCES
- 11. GPS DEVICE ARCHITECTURE Fig: GPS Device Architecture
- 12. CELLULAR GSM DATA AND TRAVEL ROUTE DETERMINATION Fig: A theoretical route (tessellated cell towers) Fig: A realistic route tessellated from cell towers
- 13. Fig: Traffic monitoring architecture
- 14. OTHER ISSUES MASS COLLECTION OF TIME-STAMPED POSITION DATA WILL REQUIRE NEW METHODOLOGIES FOR ITS STORAGE, INTERROGATION AND SUMMARIZATION. SAMPLING (AND DATA ACCURACY) POST-COLLECTION STATISTICAL ANALYSIS INFORMATION PRIVACY INTELLECTUAL PROPERTY RIGHTS STORAGE
- 15. ‘NEW DATA’ PROVIDERS AND NEW DATA INITIATIVES THERE ARE ALSO A RANGE OF CROWD-SOURCING PLATFORMS ENABLING ROAD USERS TO SHARE TRAFFIC INFORMATION FROM MOBILE DEVICES, E.G. WAZE, BEATTHETRAFFIC, WHICH ARE ALSO INCLUDED AS A SOURCE. IN AUSTRALIA, THERE ARE SOME COMPANIES PROVIDING CONVENTIONAL TRAFFIC DATA COLLECTION SERVICES (E.G. AUSTRAFFIC AND SKYHIGH TRAFFIC DATA) USING VARIOUS LEVELS OF TECHNOLOGY
- 16. PRIVATE SECTOR TRAFFIC DATA PROVIDERS • WORLD-WIDE DIGITAL TRANSPORT DATA AND INFORMATION SERVICE PROVIDERS —INCLUDING APPS. HERE (WWW.HERE.COM, FORMERLY NAVTEQ/NOKIA MAPS) • INRIX (WWW.INRIX.COM) • AIRSAGE (WWW.AIRSAGE.COM) • TOMTOM (WWW.TOMTOM.COM) • GOOGLE (MAPS.GOOGLE.COM) – INCLUDING WAZE (APP) (WWW.WAZE.COM) • SUNA GPS TRAFFIC UPDATES (HTTP://WWW.SUNATRAFFIC.COM.AU) • NAVIGON USA ( APP) (HTTP://WWW.NAVIGON.COM/PORTAL/SITES.HTML) • MOTIONX GPS DRIVE ( APP) (HTTP://NEWS.MOTIONX.COM)
- 17. Vehicle detection techniques Model based detection Region based detection Active contour based detection Feature based detection
- 18. A REAL TIME TRAFFIC MONITORING SYSTEM Feature based tracking algorithm •Camera calibration •Feature detection •Vehicle tracking •Feature grouping Benjamin Coifman, Jitendra Malik, David Beymer
- 19. DRAWBACKS GSM NETWORKS DON’T WORK WELL IN THE URBAN AREAS TEMPORARY FAULTS OF SENSOR SENSOR DATA ARE MISSING FOR SOME DAYS DUE TO THE PROBLEM IN THE RECORDING SYSTEM TOLL DATA ARE PARTLY MISSING ON WEEKENDS & HOLIDAYS
- 20. CONCLUSION RECENT AND EMERGING TECHNOLOGIES OFFER SIGNIFICANT OPPORTUNITIES FOR COLLECTING MORE INFORMATION, MORE COST EFFECTIVELY, ABOUT PERSONAL TRAVEL ACTIVITY AND ROAD USE, THAT CAN BETTER INFORM DAY-TO-DAY NETWORK MANAGEMENT, LONG-TERM INFRASTRUCTURE PLANNING AND ROAD USER TRAVEL CHOICES. GPS, GSM AND BLUETOOTH TECHNOLOGIES PROVIDE OPPORTUNITIES FOR COLLECTING MORE INFORMATION ABOUT WHEN AND WHERE VEHICLES USE THE ROAD NETWORK.